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survshap
SurvSHAP(t): Time-dependent explanations of machine learning survival modelsWildNLP
pyBreakDown
Python implementation of R package breakDownMI2DataLab_Seminarium
Materiały z seminariów prowadzonych w MI^2 DataLabie.XAI-tools
memr
R package for Multisource Embeddings for Medical RecordsResponsibleML-UseR2021
Materials for ,,Introduction to Responsible ML at UseR!2021''ResponsibleML-UseR2022
Materials for ,,Introduction to Responsible ML at UseR!2022''survxai
Explanations for survival modelsSwinSMT
Code snippets for "Swin SMT: Global Sequential Modeling for Enhancing 3D Medical Image Segmentation"modelDown_example
examples for modelDown, package that turns model into HTML pagesHADES
A powerful tool for comparing similarly structured documentsrashomon-quartet
Performance is not enough: the story of Rashomon's quartetfooling-partial-dependence
Fooling Partial Dependence via Data Poisoning (ECML PKDD 2022)MI2-prace-dyplomowe
Find out more at: http://mi2.mini.pw.edu.pl/tidycharts
https://mi2datalab.github.io/tidycharts/LIMEcraft
LIMEcraft: Handcrafted superpixel selectionand inspection for Visual eXplanationsMI2-DobreRady
Zbiór rzeczy o których warto pamiętać przygotowując pracę dyplomową lub przygotowując się do obronycrs19-monitor
Monitor of SARS-CoV-2 variants and mutationsnlp_interpretability_framework
Are you tough enough? Framework for Robustness Validation of Machine Comprehension SystemsSeFNet-Healthcare
This repository contains code and resources that can be used to reproduce the results presented in the article "SeFNet: Bridging Tabular Datasets with Semantic Feature Nets"rai-covid
Responsible Prediction Making of COVID-19 Mortality (AAAI 2021)call-for-collaborators
Summer projects in the MI2 DataLabKRAB_ZNF
KRAB-ZNF explorer - expression of KRAB-ZNF- transcription factors in The Cancer Genome Atlas studyelo-based-measure
Rashomon-detect
Rashomon-detect algorithmceterisParibusExt
Experimental Extensions for Ceteris Paribus Packagedisco-nmt
Context-aware NMT a.k.a. DISCOurse NMTSemantic-metaNet
autoexplainer
Automated explanation selection for convolutional neural networksinterpret-time-to-event
survival-xai-tutorial
Materials for tutorial: Dancing with censored data: how to survive with explainable survival analysis? at MLinPL 2023Love Open Source and this site? Check out how you can help us